Method and device for lane keeping support in motor vehicles

ABSTRACT

Method for lane keeping support in motor vehicles, in which a setpoint value for the lateral position of the vehicle is determined, the actual position of the vehicle in relation to the boundaries of the lane in which the host vehicle is traveling is detected by a sensor device and an output signal for the lane keeping support is calculated by a setpoint-actual comparison, wherein objects are tracked in at least one neighboring lane and a setpoint value for the lateral position is varied as a function of tracking data of these objects.

FIELD OF THE INVENTION

The present invention relates to a method for lane keeping support inmotor vehicles, in which a setpoint value for the lateral position ofthe vehicle is determined, the actual position of the vehicle isdetected by a sensor device in relation to the boundaries of the lane inwhich the vehicle is traveling and an output signal for the lane keepingsupport is calculated by a setpoint/actual comparison. The presentinvention also relates to a device for performing this method.

BACKGROUND INFORMATION

Systems which support the driver in driving the vehicle or whichfacilitate special driving maneuvers (advanced driver assistancesystems; ADAS) are being used to an increasing extent in motor vehicles.Lane keeping support (LKS) is a function of these systems in which theactual position of the vehicle is determined in relation to the lane inwhich the vehicle is traveling and is compared with a setpoint valuewhich typically corresponds to the center of the lane. The output signalis then composed of an actuator signal for an actuator which intervenesin the steering system of the vehicle, whether to support the driver byproviding additional steering torque or to perform a completelyautonomous lane keeping maneuver which does not require any interventionon the part of the driver.

SUMMARY

An object of the present invention is to provide a method for lanekeeping support which will correspond largely to the typical drivingbehavior of drivers.

This object may be achieved according to the present invention in thatobjects in at least one neighboring lane are tracked and the setpointvalue of the lateral position is varied as a function of the trackingdata of these objects.

It is consistent with the natural intuitive performance of a driver notto stay in the center of the lane in which he is driving but instead tochange positions in the lane depending on the traffic situation. Forexample, many drivers tend to drive slightly to the left of the centerof the lane when passing a slower vehicle in the neighboring lane on theright in order to thereby allow a greater safety distance from thevehicle being passed. Likewise many drivers tend to drive slightly tothe right of the center of the lane when they are being passed or when avehicle is approaching from the opposite direction if the oncoming laneis not separated from the host vehicle's lane by guardrails or the like,e.g., in construction areas on highways. The example method according tothe present invention simulates this natural behavior of drivers. Thisnot only yields an actual increase in driving safety but in particularit also takes into account the driver's feeling of safety and thusincreases the driver's comfort as well as increasing the confidence ofthe driver and the occupants of the vehicle in the ADAS system, whichconsequently increases the acceptance of such systems.

Performing this example method requires an object detection devicecapable of supplying tracking data regarding the objects in theneighboring lanes. However, the required hardware for such an objectdetection device is usually available anyway in vehicles having ADASsystems. For example, the sensor device which is used for determiningthe actual position of the vehicle in relation to the boundaries of thelane is frequently a camera system, e.g., one or more video cameras incombination with a (stereo) image processing system. In this case thetracking data regarding objects in neighboring lanes may also besupplied by the image processing system.

Generally, in addition to the lane keeping system, the ADAS system alsoincludes another subsystem for the longitudinal guidance support, e.g.,in the form of an ACC system (adaptive cruise control). As part of sucha system, the distances and relative speeds of vehicles traveling aheadin the host vehicle's lane and also in neighboring lanes are detectedwith the help of a direction-sensitive distance sensor, e.g., a radarsensor or a lidar sensor, and the speed of the host vehicle isautomatically adjusted, so that the vehicle traveling directly in frontis followed at an appropriate safety distance. For tracking objects inneighboring lanes, the signals of such a distance sensor may be used—incombination with the data supplied by the image processing system, ifnecessary. The relative speeds of oncoming vehicles or vehiclestraveling in front are directly measurable with the help of a distancesensor in particular, so the traffic situation may be extrapolated onthe basis of the measured relative speeds extrapolated into the futurevery easily and precisely, so that “evasive maneuvers” to be performedby the method according to the present invention may be initiated in atimely manner.

If the traffic behind the host vehicle is also observed with the help ofthe camera system and/or with the help of a rearview radar or all-roundradar, then it is also possible to take into account passing maneuversof following vehicles in a timely manner.

The extent of the shift in the setpoint value from the center of thelane, i.e., the ideal line, preferably depends on one or more of thefollowing parameters: lateral distance from the object tracked in theneighboring lane, the size and type of this object, the position of theobject in the right or left neighboring lane, the object distance alongthe lane, the speeds of the host vehicle and the object detected, i.e.,the relative speed of the object, and the width of the lane. Ifnecessary, visibility and weather conditions may also be taken intoaccount. For example, if the road is wet, a greater lateral offset mightbe preferably selected to prevent impaired visibility due to the splashthrown up by vehicles in neighboring lanes. The visibility and weatherconditions as well as similar parameters may be detected eitherautomatically or on command by the driver.

It is also possible for the driver to have the option to select acertain setpoint lateral offset of the host vehicle from the center ofthe lane, e.g., to be able to see better past any lead vehiclesregardless of the presence of objects in the neighboring lanes. In thiscase, the “normal” lateral offset selected by the driver is also takeninto account in determining the setpoint value for the lateral positionas a function of objects in the neighboring lanes.

The parameters which determine the precise response of the vehicle toobjects located in the neighboring lanes are also influenceable withincertain limits, taking into account safety aspects, through suitableconfiguration commands by the driver.

According to a refinement of the present invention, it is also possibleto implement this method as an adaptive system which automaticallyadapts to the driver's performance. This is true in particular for thecase of lane keeping support in the actual sense, i.e., for the casewhen the driver himself retains control of the steering system and theactuator of the lane keeping system intervenes merely as a supportivemeasure by injecting a supplementary steering torque into the steering.In this case, the driver is able to override the automatic lane keepingby “countersteering” or “holding.” The extent of “holding” by the driverthen forms a feedback signal which makes it possible to automaticallyadapt the behavior of the lane keeping system to the intents andpreferences of the driver.

Lane keeping systems are frequently designed to allow a certain cuttingof the turn when negotiating turns. This may be done, for example, bycalculating an ideal line which deviates from the center of the laneand/or by calculating a setpoint value for the lateral position(corresponding to the center of the lane or the ideal line) for acertain point which is situated at a speed-dependent distance ahead ofthe current position of the vehicle. This distance (predicted distance)is often indicated in the form of a time interval (predicted time),which is given by the quotient of the predicted distance and theabsolute speed of the vehicle. Intervention in the steering is thenperformed by making the actual value for the lateral position of thevehicle within the predicted time match the setpoint value. Whennegotiating turns, this regulated behavior necessarily results in theturns being cut to some extent, which depends on the predicted distance.In the method according to the present invention, the setpoint value forthe lateral position and/or the predicted distance should be adjusted sothat when there is oncoming traffic or when vehicles are in the leftneighboring lane, turn cutting is suppressed for left turns, andsimilarly, when there are vehicles in the right neighboring lane, turncutting is suppressed for right turns.

An exemplary embodiment is explained in greater detail below withreference to the figures.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows a block diagram of a lane keeping system for a motorvehicle.

FIG. 2 shows a diagram to illustrate the principles of an example methodaccording to the present invention.

FIG. 3 shows a flow chart of the example method according to the presentinvention.

FIGS. 4 and 5 show examples of weighting functions which are used in theexample method according to FIG. 3.

FIG. 6 shows a diagram illustrating the example method in negotiatingturns.

DETAILED DESCRIPTION OF EXAMPLE EMBODIMENTS

FIG. 1 shows schematically a top view of a motor vehicle 10 which istraveling in a lane 16 of a multilane road defined by boundaries 14 witha slight lateral offset from center 12 of the lane. Longitudinal axis 18of motor vehicle 10 is shown with a dash-dot line, and the lateraldeviation between longitudinal axis 18 and center 12 of the lane islabeled as ΔY.

Motor vehicle 10 is equipped with an ADAS system, which includes as asubsystem a lane keeping system having the following components,depicted in the form of a block diagram: a sensor device which includesa video camera 20 and an image processing unit 22, an object recognitiondevice 24, a selection device 26 for selecting a setpoint valueΔY_(setpoint) for the lateral position of motor vehicle 10, a processingdevice 28 and a steering actuator 30 which is triggered by an outputsignal A of processing device 28 and intervenes in the vehicle steeringto regulate the lateral position of motor vehicle 10 at the setpointvalue.

In the example shown here, the actual position of the vehicle in thedirection across longitudinal axis 18 is detected using the sensordevice formed by video camera 20 and image processing unit 22. Imageprocessing unit 22 therefore analyzes the video image recorded by thecamera to recognize boundaries 14 and the position of motor vehicle 10in relation to these boundaries. This embodiment of the sensor device isto be understood only as an example and may be replaced by magneticsensors, for example, which detect magnetic markers as the boundaries ofthe road. Likewise, the boundaries of the road could also be marked byreflectors detected by a radar system of the vehicle.

If the position of two boundaries 14 in relation to motor vehicle 10 isknown, then the width of lane 16 and the location of center 12 of thelane may also be determined from this data. The sensor device istherefore able to relay to processing device 28 the actual position ofmotor vehicle 10, expressed by an actual value ΔY_(actual) of lateraldeviation ΔY. On the basis of a comparison of actual value ΔY_(actual)with setpoint value ΔY_(setpoint), processing device 28 then formsoutput signal A, which is sent to steering actuator 30. Setpoint valueΔY_(setpoint) is also expressed as a lateral deviation from center 12 ofthe lane. For example, positive values of ΔY_(setpoint) correspond to adeviation from center 12 of the lane to the right and negative valuescorrespond to a deviation from the center of the lane to the left.

Selection device 26 includes a memory 32 in which a normal value ΔY_(n)of the setpoint value desired by the driver is stored. Selection device26 also includes a setting element 34 on the steering wheel of thevehicle using which the stored normal value is variable. In this way thedriver of vehicle 10 is able to select lateral deviation ΔY individuallyaccording to his own personal preferences or needs. However, selectiondevice 26 may be designed to modify the setting made by the driver or tolimit the range of settings. For example, it is expedient to limit thesetting range as a function of the width of the lane measured with thehelp of the sensor device and as a function of the known width of thevehicle, so the vehicle always maintains an adequate safety distancefrom the boundaries of the lane. It is also possible for the settingperformed with the help of setting element 34 not to give lateraldeviation ΔY in a fixed unit of length but instead as a percentage basedon the width of the lane or on the excess width of the lane, i.e., thedifference between the width of the lane and the width of the vehicle.In this case, the setpoint value stored in memory 32 would be adaptedautomatically when the width of the lane changes without the driverhaving to adjust setting element 34.

Object recognition device 24, which is shown as a separate block in FIG.1, is part of image processing unit 22, which is designed specificallyfor recognizing objects in neighboring lanes next to lane 16 on whichhost vehicle 10 is traveling. FIG. 1 shows a right neighboring lane 36in which another vehicle as object 38 is traveling. Object recognitiondevice 24 extracts from the video image tracking data for object 38which includes in particular the position of this object plus, ifnecessary, its type and size. Among other things, this tracking dataincludes lateral distance Y_(r) of object 38 from center 12 of lane 16.In the example shown here, Y_(r) denotes the smallest lateral distancefor objects in right neighboring lane 36, i.e., the distance betweencenter 12 of the lane and the left vehicle boundary of object 38.

In addition, information regarding the longitudinal position of object38 along lane 36 and regarding the relative speed of object 38 inrelation to vehicle 10 may also be extracted from the video image. Inthe example shown here, however, vehicle 10 is additionally equippedwith a radar sensor 40. This radar sensor 40 is used primarily fordetecting lead vehicles in lane 16 and for regulating the distance aspart of a longitudinal guidance system. However, it may also supplyinformation regarding objects in neighboring lanes, in particularregarding the longitudinal distance and relative speed of these objects,as well as, given adequate angular resolution, lateral distance Y_(r).By comparing the information supplied by video camera 20 and radarsensor 40, the accuracy and reliability of the tracking may be improved.If object 38 enters the blind spot of video camera 20 and radar sensor40 in a passing maneuver, the tracking data for the object may beextrapolated on the basis of the relative speed under the assumptionthat object 38 is remaining in its lane position in neighboring lane 36.To improve object tracking, additional sensor components may optionallybe provided, e.g., additional video cameras, an all-round radar and thelike.

Similarly, objects in a left neighboring lane (not shown in FIG. 1) mayalso be tracked with the help of the tracking system. If multipleobjects are being tracked, object recognition device 24 supplies a setof tracking data including lateral distances Y_(r,i) to selection device26 for each object detected. On the basis of this tracking data,selection device 26 calculates setpoint value ΔY_(setpoint) for thelateral position of vehicle 10. If necessary, normal value ΔY_(n) storedin memory 32 is modified so that when passing object 38, a greatersafety distance from this object is maintained.

This adaptation of the setpoint value and the resulting vehicleperformance is illustrated in FIG. 2 on the basis of an example.

FIG. 2 shows motor vehicle 10 in lane 16 and a truck 42 and a passengervehicle 44 as objects in neighboring lane 36 on the right. In addition,FIG. 2 shows two lanes 46 and 48 of oncoming traffic. Lane 48 directlyadjacent to lane 16 is delimited from lane 16 only by a lane marker andis regarded here as a neighboring lane. In the example shown here, twopassenger vehicles are traveling on it, these vehicles likewise beingtracked by object recognition device 24 as objects 50, 52. However, avehicle 54 traveling in lane 46 is no longer being tracked as a relevantobject.

Center 12 of lane 16 is shown with a dash-dot line and the path ofvehicle 10 is given as a dashed line, this path being determined bysetpoint values ΔY_(setpoint) which are determined periodically byselection device 26.

It is assumed here that normal value ΔY_(n) has been set at 0 by thedriver, i.e., the setpoint value corresponds to center 12 of the lane ifthere are no objects in neighboring lanes 36 and 48. When vehicle 10approaches truck 42, ΔY_(setpoint) becomes negative, i.e., the vehiclewill travel slightly to the left of center 12 of the lane in order tomaintain a greater safety distance from the truck. After passing truck42, passenger vehicle 44 is passed next. However, the lateral offset ofpath 56 is then reduced almost to 0 again because object 50 is nowapproaching vehicle 10 from the opposite direction. Because of the muchgreater relative speed, a greater relative safety distance should bemaintained with respect to the oncoming vehicle. Although passengervehicle 44 has been passed, ΔY_(setpoint) is positive, the host vehicleis traveling with a lateral offset to the right in relation to center 12of the lane because neighboring lane 36 on the right is then free and agreater safety distance should be maintained from object 52, which inthis case is an oncoming object.

According to one exemplary embodiment, the method for lane keepingsupport could take place approximately as follows. A certain predictedtime T_(v) is used as the basis for regulating the lateral position.Setpoint value ΔY_(setpoint) is calculated in each case by selectiondevice 26 for a point on road 16 which is reached by vehicle 10 afterpredicted time T_(v). Output signal A is calculated by processing device28 accordingly, so the setpoint-actual deviation within predicted timeT_(v) is reduced to 0.

For each tracked object 42, 44, 50, 52, selection device 26 calculateson the basis of the measured longitudinal distance and the relativespeed of the object a point in time T_(pa) when vehicle 10 will begin topass the object in question. In the case of truck 42, T_(pa) is thepoint in time when the front end of vehicle 10 reaches the rear edge oftruck 42. Similarly, a point in time T_(pe) when the passage of theobject is concluded is calculated for each object. In the case of truck42, this is the point in time when the rear bumper of vehicle 10 islevel with the front bumper of truck 42. FIG. 2 shows the positions ofthe front bumper of vehicle 10 for points in time T_(pa) and T_(pe).Vehicle 10 is shown with a dashed line at the point in time whenpredicted time T_(v) corresponds to calculated time T_(pa) (however,truck 42 has not yet reached the position shown in FIG. 2 at this pointin time but instead reaches this position only after predicted timeT_(v) has elapsed). When vehicle 10 has reached the position shown withthe dashed line, selection device 26 calculates setpoint valueΔY_(setpoint) taking into account truck 42. At this point in time thesteering intervention is initiated on the basis of output signal A,causing the lateral position of vehicle 10 to correspond to thecalculated setpoint value at point in time T_(pa).

If vehicle 10 and truck 42 are level with one another, selection device26 would calculate setpoint value ΔY_(setpoint) for a point in timewhich is later by T_(v). If passenger vehicle 44 were not present, thesetpoint value would be returned to 0 at this point in time. The resultwould be that vehicle 10 would already be approaching truck 42 beforethe passing maneuver is in fact concluded. According to one exampleembodiment of the present invention, this is preventable by reducingpredicted time T_(v) to a smaller value—at least with respect to object42 which is currently of relevance, so that the return to the center ofthe lane occurs later accordingly. However, the normal (longer)predicted time should remain in effect in consideration of other objects44, 50 and 52. In a modified embodiment, the setpoint value calculatedwith respect to a certain object (i.e., truck 42 here) is retained untilthis object has in fact been passed, i.e., until time T_(pe).

FIG. 3 shows a flow chart for this latter variant of the method, takinginto account objects in both neighboring lanes 36 and 48.

The program routine illustrated by the flow chart in FIG. 3 is retrievedperiodically at short intervals, e.g., every 10 ms. In step S1, pointsin time T_(pa) and T_(pe) (when the passage of the particular objectbegins and ends, respectively) are calculated for all objects tracked,i.e., for objects 42, 44, 50 and 52 in FIG. 2. In step S2, a check isperformed to determine whether conditions T_(pa)≦T_(v) and T_(pe)<0 aremet for at least one object in the neighboring lane on the right. Thefirst condition means that passage of the object will begin within timeT_(v). The second condition means that passage of the object is not yetconcluded. If both conditions are met, setpoint value ΔY_(setpoint) forthe lateral position should consequently be calculated as a function ofthe tracking data of this object. Accordingly, in step S3 a value ΔY_(r)is calculated, namely as a doubled function w_(r)(Y_(r)) of lateraldistance Y_(r) of the particular object. Function value w_(r)(Y_(r)) isa candidate for the setpoint value and would be accepted as the finalsetpoint value if that particular object were the only relevant objectin the neighboring lane on the right.

If the conditions queried in step S2 for two objects are met in theneighboring lane on the right, step S3 is performed for both objects andthen the smaller of the two resulting values is used for ΔY (smallervalues for the setpoint value correspond to a greater lateral offset tothe left). This situation could occur, for example, when the passingmaneuver for truck 42 is not yet concluded but passenger vehicle 44 isreached in less than time T_(v).

If the conditions queried in step S2 are not met for any object in theright neighboring lane, then ΔY_(r) is set at normal value ΔY_(n) instep S4; depending on the driver's instructions, this normal value maybe positive or negative corresponding to a desired deviation from thecenter of the lane to the right or left.

Subsequent steps S5, S6 and S7 are a repetition of steps S2-S4, but inthis case for objects in the left neighboring lane. In step S6, doubledfunction value w_(l)(Y_(l)) is calculated as a value ΔY₁, which is alsoa candidate for the setpoint value and forms the final setpoint valuewhen only objects in the left lane are to be taken into account.

In step S8 final setpoint value ΔY_(setpoint) is then calculated byforming the average of values ΔY_(r) and ΔY_(l). This setpoint value isthen used as the basis for calculations in processing device 28.

It should first be assumed that ΔY_(n) has been set by the driver at 0.In this case final setpoint value ΔY_(setpoint) is equal to w_(r)(Y_(r))when only one relevant object has been located in the right neighboringlane and it is equal to w_(l)(Y_(l)) when only one relevant object hasbeen located in the left neighboring lane. If relevant objects have beenlocated in both neighboring lanes, the final setpoint value represents acompromise between candidates w_(r)(Y_(r)) and w_(l)(Y_(l)). Thiscompromise corresponds to path 56 in FIG. 2 with simultaneous passing ofpassenger vehicles 44 and 50.

If ΔY_(n) is not equal to zero and the conditions queried in steps S2and S5 are not met either for the right or left neighboring lanes, thenfinal setpoint value ΔY_(setpoint)=ΔY_(n), i.e., the lateral offset ofthe vehicle in relation to center 12 of the lane corresponds to thedriver's intent. If only the query in step S2 or only the query in stepS5 had a positive outcome, then the final setpoint value in step S8 willbe modified slightly, i.e., by ΔY_(n)/2. This may be quite desirable tomoderate excessive lateral movements of the vehicle. However, theprogram may optionally be modified so that ΔY remains completelydisregarded when one of the queries in step S or S5 has a positiveoutcome.

Functions w_(r) and w₁ denote the setpoint value displacement as afunction of relative speed V_(r) of the particular object.

Examples of these functions are shown in FIGS. 4 and 5. The dependenceon the relative speed takes into account the idea that the safetydistance should be greater at a greater relative speed. As FIG. 4 shows,function w_(r)(Y_(r)) begins at a certain (positive or negative) initialvalue (at V_(r)=0) and then approaches asymptotically a certain minimumvalue w_(min). Value w_(min) depends on the width of lane 16 and isselected so that the greatest possible distance from the object ismaintained at a very great relative speed but without vehicle 10 leavinglane 16.

The initial value at relative speed 0 is given by MIN(ΔY_(n), Y_(r)−w₀),where w₀ is a minimum safety distance from the particular object; thedistance should never be less than this minimum distance. If lateraldistance Y_(r) of the object in the neighboring lane on the right isvery great, then the initial value is given ΔY_(n), i.e., the object hasno influence on the lateral offset desired by the driver. Only at a verylow value of lateral distance Y_(r) of the object is the initial valuegiven by Y_(r)−w₀ and selected so that the object passes at least at adistance w₀. When the tracked object leaves the neighboring lane andchanges to lane 16 in which the host vehicle is traveling, Y_(r)−w₀assumes very small negative values and may even fall below w_(min). Inthis case, safety distance w₀ may no longer be maintained and acollision warning should be output to the driver.

FIG. 5 shows function w_(l)(Y_(l)) constructed according to similarprinciples for objects in the neighboring lane on the left. Thisneighboring lane on the left may be a lane of the road with traffic inthe same direction or a lane of oncoming traffic (as in FIG. 2). In thelatter case, relative speeds V_(r) are higher in general.

Functions w_(r) and w_(l) may be stored as function specifications withsuitable parameters, as tables or as characteristic maps in memory 32 ofselection device 26. These functions may also depend on the absolutespeed of vehicle 10, e.g., in such a way that the function values andthus the corresponding lateral offset of the vehicle are smaller inabsolute value at higher absolute speeds, so that uncomfortably hightransverse accelerations may be avoided when passing at a high speed.

If the driver intervenes manually in the steering to force a lateraloffset from center 12 of the lane that is greater or smaller than thesetpoint value calculated in step S8, then the parameters that determinefunctions w_(r) and w_(l) may be adapted so that the setpoint valuecalculated in step S8 corresponds to the driver's intent, which isdiscernible on the basis of the driver's steering maneuver.

With the example method described above it is possible to keep predictedtime T_(v) constant. When negotiating turns, however, it is expedient tovary the predicted time and the predicted distance accordingly, which isobtained by multiplying the predicted time by the absolute speed ofvehicle 10. This is illustrated in FIG. 6, which shows vehicle 10 on acurved section of road. A dash-dot arrow 58 here indicates the predicteddistance which results from regular predicted time T_(v). This wouldyield a path 60 of vehicle 10, which is indicated by a thin dotted linein FIG. 6.

This shows that the long predicted time results in a certain cutting ofthe turn. If no object is present on neighboring lane 36 at the right,this cutting of the turn is quite acceptable. However, if there is anobject 38 in the neighboring lane, there may be a problematical approachto this object even if the setpoint value has been offset laterally tothe left because of the tracking of object 38. If an object in the innerneighboring lane is tracked in a turn, it is expedient to shorten thepredicted time and thus also the predicted distance as indicated by anarrow 62 in FIG. 6. Resulting path 64 of vehicle 10 ensures that anadequate distance from object 38 will always be maintained.

The processing procedures necessary for the method according to thepresent invention may be performed by a microcomputer, for example,which fulfills the functions of selection device 26 and processingdevice 28 in FIG. 1. If no camera system is available for objectrecognition, the tracking data may also be obtained via radar sensor 40or a comparable distance sensor, e.g., a lidar sensor. The size of theobject tracked may then be estimated at least approximately on the basisof the dependence on the direction and/or the strength of the echosignal so that a distinction may be made at least between a truck 42 anda passenger vehicle 44. Standard values for the various object classes(passenger vehicle or truck) may be used as the basis for the length ofthe object which is needed for determining point in time T_(pe). In thecase of a truck, echo signals originating from reflections on the frontfender or other structures of the truck may also be analyzed, ifnecessary. In a simplified embodiment, a constant, sufficiently greatobject length may always be used as the basis for calculations.

1. A method for lane keeping support in a motor vehicle, the methodcomprising: determining a setpoint value for a lateral position of thevehicle relative to a center of a lane in which the vehicle istraveling, wherein the determined setpoint value is such that thevehicle remains inside the lane when the position of the vehicle iscontrolled according to the setpoint value; determining an actualposition of the vehicle in relation to boundaries of the lane in whichthe vehicle is traveling, using a sensor device; calculating an outputsignal for the lane keeping support by a setpoint-actual comparison;controlling the position of the vehicle according to the setpoint value,using the output signal; and tracking at least one object in at leastone neighboring lane and varying the setpoint value, for the lateralposition of the vehicle relative to the center of the lane, as afunction of tracking data of the object, wherein the varied setpointstill keeps the vehicle inside the lane when the position of the vehicleis controlled according to the setpoint value; wherein the determinedsetpoint value is a control parameter for providing control of thevehicle position; wherein the setpoint value is calculated as a functionof a normal value selectable by a driver and representing a lateraloffset of the vehicle from a center of the lane in which the vehicle istraveling, as desired by the driver.
 2. The method as recited in claim1, wherein the tracking data includes a lateral distance of the objectfrom a center of the lane in which the vehicle is traveling or from thelateral position of the vehicle, and wherein the setpoint value isvaried by increasing the lateral distance when passing the object. 3.The method as recited in claim 1, wherein the tracking step includesanalyzing a video image recorded by at least one video camera.
 4. Themethod as recited in claim 1, further comprising: acquiring the trackingdata of the object using a distance sensor.
 5. The method as recited inclaim 4, wherein the distance sensor is one of a radar sensor or a lidarsensor.
 6. The method as recited in claim 1, wherein an object in aneighboring lane on a right of the vehicle and an object in aneighboring lane on a left of the vehicle are tracked, one of theneighboring lanes on the right or left being a lane of oncoming traffic.7. The method as recited in claim 1, wherein the tracking data includesat least one of an object distance in a longitudinal direction of thelane in which the vehicle is traveling, an absolute or relative speed ofthe object, and a size of the object, and wherein the setpoint value iscalculated taking into account at least one of the tracking data.
 8. Themethod as recited in claim 1, further comprising: dynamically varying atleast one of parameters which determine a dependence of the setpointvalue on the tracking data by a self-learning system as a function ofcorrecting measures taken by the driver in steering.
 9. The method asrecited in claim 1, wherein the output signal is calculated in such away that the actual position is regulated at the setpoint value within afixedly or variably selectable predicted time.
 10. The method as recitedin claim 9, wherein points in time at which the vehicle will pass theobject are calculated in advance based on measured relative speeds ofthe object, and the tracking data of the passed objects after thepredicted time has elapsed is used for calculation of the setpointvalue.
 11. The method as recited in claim 10, wherein the predicted timeis reduced while the object is being passed in passing maneuvers. 12.The method as recited in claim 11, wherein the predicted time is reducedin curves.
 13. A device for lane keeping support in a motor vehicle,comprising: a device configured to determine a setpoint value for alateral position of the vehicle relative to a center of a lane in whichthe vehicle is traveling, wherein the determined setpoint value is suchthat the vehicle remains inside the lane when the position of thevehicle is controlled according to the setpoint value; a sensor deviceconfigured to detect an actual position of the vehicle in relation toboundaries of the lane in which the vehicle is traveling; a comparatordevice to calculate an output signal for the lane keeping support by asetpoint value-actual comparison; a control device to control theposition of the vehicle according to the setpoint value, using theoutput signal; a tracking system configured to track objects in at leastone neighboring lane; and a device to vary the setpoint value, for thelateral position of the vehicle relative to the center of the lane, as afunction of the tracking data of these objects, wherein the variedsetpoint still keeps the vehicle inside the lane when the position ofthe vehicle is controlled according to the setpoint value; wherein thedetermined setpoint value is a control parameter for providing controlof the vehicle position; wherein the setpoint value is calculated as afunction of a normal value selectable by a driver and representing alateral offset of the vehicle from a center of the lane in which thevehicle is traveling, as desired by the driver.
 14. The method of claim1, wherein the object is a second vehicle moving in the at least oneneighboring lane.
 15. The method of claim 14, wherein the tracking dataincludes the size of the second vehicle moving in the at least oneneighboring lane, and the varying of the setpoint value includes varyingthe setpoint value as a function of the size of the second vehiclemoving in the at least one neighboring lane.
 16. The method of claim 14,wherein the setpoint value has a first magnitude prior to the vehiclepassing the second vehicle when the vehicle is not within apredetermined longitudinal distance of the second vehicle, and whereinthe setpoint value is varied to a second magnitude as a function of thetracking data when the vehicle is within the predetermined longitudinaldistance from the second vehicle, and further comprising returning thesetpoint value to the first magnitude after the vehicle has passed thesecond vehicle and the vehicle is again not within the predeterminedlongitudinal distance from the second vehicle.
 17. The method of claim6, wherein the object in the neighboring lane on the right of thevehicle is a second vehicle and the object in the neighboring lane onthe left of the vehicle is a third vehicle, and the setpoint value isvaried as a function of the tracking data of both the second and thirdvehicles.
 18. The method of claim 17, wherein the setpoint value isvaried as a function of an average of a first setpoint value and asecond setpoint value, the first setpoint value calculated as a functionof the tracking data of the second vehicle, and the second setpointvalue calculated as a function of the tracking data of the thirdvehicle.